Proof of Commitment: A Human-Centric Resource for Permissionless Consensus

TL;DR

This work tackles the challenge of Sybil resistance in permissionless consensus by replacing machine-dominated scarcity (computation, capital) with a non-parallelizable, human-time resource. It introduces PoCmt, a protocol where validator influence is derived from a decomposed commitment state and a Human Challenge Oracle that binds identity to bounded human effort, yielding a linear Sybil cost $\Theta(sT)$ for maintaining $s$ identities over $T$ epochs. The authors prove a cost-theoretic separation from parallelizable-resource protocols, establish backbone-style safety and liveness under partial synchrony, and validate the approach via simulations that isolate human-time capacity as the adversarial bottleneck. PoCmt thus expands the consensus design space by anchoring security in sustained human participation, with practical considerations around incentives, usability, and adaptive challenge design for real deployments.

Abstract

Permissionless consensus protocols require a scarce resource to regulate leader election and provide Sybil resistance. Existing paradigms such as Proof of Work and Proof of Stake instantiate this scarcity through parallelizable resources like computation or capital. Once acquired, these resources can be subdivided across many identities at negligible marginal cost, making linear Sybil cost fundamentally unattainable. We introduce Proof of Commitment (PoCmt), a consensus primitive grounded in a non-parallelizable resource: real-time human engagement. Validators maintain a commitment state capturing cumulative human effort, protocol participation, and online availability. Engagement is enforced through a Human Challenge Oracle that issues identity-bound, time-sensitive challenges, limiting the number of challenges solvable within each human window. Under this model, sustaining multiple active identities requires proportional human-time effort. We establish a cost-theoretic separation showing that protocols based on parallelizable resources admit zero marginal Sybil cost, whereas PoCmt enforces a strictly linear cost profile. Using a weighted-backbone analysis, we show that PoCmt achieves safety, liveness, and commitment-proportional fairness under partial synchrony. Simulations complement the analysis by isolating human-time capacity as the sole adversarial bottleneck and validating the predicted commitment drift and fairness properties. These results position PoCmt as a new point in the consensus design space, grounding permissionless security in sustained human effort rather than computation or capital.

Figures (4)

• Figure 1: Commitment drift under human-time scarcity. Total honest and adversarial commitment weights, $W_H(t)=\sum_{v\in H}CS_v(t)$ and $W_A(t)=\sum_{a\in A}CS_a(t)$, over time. Honest commitment grows approximately linearly since honest validators solve challenges and remain online with high probability, while the adversary is constrained by a fixed human-time capacity $m$ (maximum number of solved HCO challenges per window). The persistent gap $W_H(t)-W_A(t)$ empirically illustrates the drift behavior predicted by Lemma \ref{['lem:drift']}.
• Figure 2: Adversarial leader share is controlled by human-time capacity. Mean adversarial leader fraction (with standard deviation across seeds) as a function of adversarial human-time capacity $m$ (solved challenges per window). Increasing $m$ increases adversarial leader share smoothly; however, achieving majority leadership requires $m$ itself to be large. This operationalizes the non-parallelizable resource claim: capital or identity replication alone cannot push leader share beyond what human-time permits (Theorem \ref{['thm:linear-sybil']}).
• Figure 3: Weight share tracks leader share under commitment-proportional sampling. Final adversarial commitment share $W_A(T)/(W_H(T)+W_A(T))$ versus human-time capacity $m$. The close agreement between weight share (this figure) and leader share (Figure \ref{['fig:capacity-leader']}) confirms that the implemented leader sampling matches the ideal commitment-proportional rule in Section \ref{['sec:leader-election']}, and supports the fairness statement of Lemma \ref{['lem:fairness']}.
• Figure 4: Fairness of commitment-weighted leader election among honest validators. For each honest validator, the x-axis reports its ideal leader probability averaged over time (proportional to $CS_v(t)$), while the y-axis shows the empirical leader frequency over the simulation horizon. Points cluster near the diagonal, indicating that leader election does not systematically bias honest nodes beyond differences in accumulated commitment, consistent with Lemma \ref{['lem:fairness']}.

Theorems & Definitions (21)

• lemma 1: Window-level linear human-time requirement
• proof : Proof sketch
• lemma 2: Sublinear human-time implies bounded adversarial weight
• proof : Proof sketch
• theorem 1: PoCmt achieves linear Sybil cost
• proof : Proof sketch
• lemma 3: Zero marginal Sybil cost
• proof
• corollary 1: Impossibility of linear Sybil cost in PoW/PoS
• definition 1: Weighted honest majority